Instructions to use Norquinal/PetrolOrca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Norquinal/PetrolOrca with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Norquinal/PetrolOrca")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Norquinal/PetrolOrca") model = AutoModelForCausalLM.from_pretrained("Norquinal/PetrolOrca") - Inference
- Local Apps Settings
- vLLM
How to use Norquinal/PetrolOrca with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Norquinal/PetrolOrca" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Norquinal/PetrolOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Norquinal/PetrolOrca
- SGLang
How to use Norquinal/PetrolOrca with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Norquinal/PetrolOrca" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Norquinal/PetrolOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Norquinal/PetrolOrca" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Norquinal/PetrolOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Norquinal/PetrolOrca with Docker Model Runner:
docker model run hf.co/Norquinal/PetrolOrca
- Xet hash:
- df89c7c04a33d6684fefb1e5dfe27b379337cb446f3040cc4a9b7bdb9a29cc18
- Size of remote file:
- 4.54 GB
- SHA256:
- 37962a8535c23fdec5d18aaf83bae74d5da4621363a87bf5344a4e981fd83cd3
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